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Source channel @githubtrending · Post #14747 · May 25
#python#deep_learning#intel#machine_learning#neural_network#pytorch#quantization Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models. https://github.com/intel/intel-extension-for-pytorch
Search: #insert
@djangoproject · Post #428 · 08/30/2017, 03:40 AM
How #Django knows to #UPDATE vs. #INSERT when you call #save (), #Django follows this algorithm: If the object’s primary key attribute is set to a value that evaluates to True (i.e., a value other than None or the empty string), Django executes an UPDATE. If the object’s primary key attribute is not set or if the UPDATE didn’t update anything, Django executes an INSERT.